CMEO: a metadata-centric ontology for clinical studies exploration and harmonization assessment
Komal Gilani, Wei Wei, Christof Peters, Marlo Verket, Hans-Peter Brunner-La Rocca, Enrico Nicolis, Martina Colombo, Katharina Marx-Schütt, Visara Urovi, Michel Dumontier

TL;DR
CMEO is a new ontology that helps integrate clinical data by harmonizing metadata across studies, enabling privacy-conscious research.
Contribution
CMEO introduces a metadata-centric ontology for harmonizing clinical study metadata and enabling semantic querying.
Findings
CMEO enables semantic querying and comparison of clinical study metadata.
Demonstrated utility with five studies, including heart failure and diabetes.
Supports FAIR-compliant integration and governance-constrained reuse of clinical data.
Abstract
The integration of clinical research data across various institutions faces hurdles due to differing definitions, inconsistent terminologies, and inadequate support for interoperable metadata. While biomedical ontologies offer valuable tools for structuring clinical data, they have not yet been fully utilized for creating comprehensive metadata descriptors, such as variable semantics, statistical summaries, and governance elements essential for data discovery and alignment. We present the Clinical Metadata Exploration Ontology (CMEO) that builds upon well-established ontologies to provide a cohesive representation of study designs, data elements, exploratory statistics, and data reuse permissions. CMEO facilitates semantic querying for study exploration and comparison of data elements across studies, particularly when individual-level data cannot be shared. We demonstrate its utility…
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
Click any figure to enlarge with its caption.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsBiomedical Text Mining and Ontologies · Research Data Management Practices · Electronic Health Records Systems
